mt5-semantic
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Rouge1: 1.0
- Rouge2: 1.0
- Rougel: 1.0
- Rougelsum: 1.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 90
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 7.1720 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 2 | 6.2006 | 0.1333 | 0.0 | 0.1333 | 0.1333 |
| No log | 3.0 | 3 | 5.7428 | 0.1333 | 0.0 | 0.1333 | 0.1333 |
| No log | 4.0 | 4 | 3.8803 | 0.1333 | 0.0 | 0.1333 | 0.1333 |
| No log | 5.0 | 5 | 5.0966 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 6.0 | 6 | 5.3543 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 7.0 | 7 | 5.1282 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 8.0 | 8 | 4.5391 | 0.2 | 0.0 | 0.2 | 0.2 |
| No log | 9.0 | 9 | 3.3062 | 0.25 | 0.0 | 0.25 | 0.25 |
| No log | 10.0 | 10 | 2.5865 | 0.25 | 0.0 | 0.25 | 0.25 |
| No log | 11.0 | 11 | 2.4655 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 12.0 | 12 | 2.0948 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 13.0 | 13 | 1.8355 | 0.25 | 0.1429 | 0.25 | 0.25 |
| No log | 14.0 | 14 | 1.5715 | 0.25 | 0.1429 | 0.25 | 0.25 |
| No log | 15.0 | 15 | 1.3096 | 0.3333 | 0.25 | 0.3333 | 0.3333 |
| No log | 16.0 | 16 | 1.1770 | 0.2105 | 0.1176 | 0.2105 | 0.2105 |
| No log | 17.0 | 17 | 1.0978 | 0.3158 | 0.2353 | 0.3158 | 0.3158 |
| No log | 18.0 | 18 | 1.2578 | 0.3158 | 0.2353 | 0.3158 | 0.3158 |
| No log | 19.0 | 19 | 1.0386 | 0.3158 | 0.2353 | 0.3158 | 0.3158 |
| No log | 20.0 | 20 | 0.7758 | 0.25 | 0.0 | 0.25 | 0.25 |
| No log | 21.0 | 21 | 0.6506 | 0.2222 | 0.125 | 0.2222 | 0.2222 |
| No log | 22.0 | 22 | 0.7023 | 0.2222 | 0.125 | 0.2222 | 0.2222 |
| No log | 23.0 | 23 | 0.6491 | 0.2222 | 0.125 | 0.2222 | 0.2222 |
| No log | 24.0 | 24 | 0.6289 | 0.2105 | 0.1176 | 0.2105 | 0.2105 |
| No log | 25.0 | 25 | 0.6138 | 0.4444 | 0.2857 | 0.4444 | 0.4444 |
| No log | 26.0 | 26 | 0.6190 | 0.4 | 0.25 | 0.4 | 0.4 |
| No log | 27.0 | 27 | 0.4749 | 0.2105 | 0.1176 | 0.2105 | 0.2105 |
| No log | 28.0 | 28 | 0.3589 | 0.25 | 0.0 | 0.25 | 0.25 |
| No log | 29.0 | 29 | 0.4597 | 0.3077 | 0.0 | 0.3077 | 0.3077 |
| No log | 30.0 | 30 | 0.3665 | 0.3077 | 0.0 | 0.3077 | 0.3077 |
| No log | 31.0 | 31 | 0.2642 | 0.3077 | 0.0 | 0.3077 | 0.3077 |
| No log | 32.0 | 32 | 0.1914 | 0.3077 | 0.0 | 0.3077 | 0.3077 |
| No log | 33.0 | 33 | 0.1114 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 34.0 | 34 | 0.0375 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 35.0 | 35 | 0.0187 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 36.0 | 36 | 0.0111 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 37.0 | 37 | 0.0046 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 38.0 | 38 | 0.0021 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 39.0 | 39 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 40.0 | 40 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 41.0 | 41 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 42.0 | 42 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 43.0 | 43 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 44.0 | 44 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 45.0 | 45 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 46.0 | 46 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 47.0 | 47 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 48.0 | 48 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 49.0 | 49 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 50.0 | 50 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 51.0 | 51 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 52.0 | 52 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 53.0 | 53 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 54.0 | 54 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 55.0 | 55 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 56.0 | 56 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 57.0 | 57 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 58.0 | 58 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 59.0 | 59 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 60.0 | 60 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 61.0 | 61 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 62.0 | 62 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 63.0 | 63 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 64.0 | 64 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 65.0 | 65 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 66.0 | 66 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 67.0 | 67 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 68.0 | 68 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 69.0 | 69 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 70.0 | 70 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 71.0 | 71 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 72.0 | 72 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 73.0 | 73 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 74.0 | 74 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 75.0 | 75 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 76.0 | 76 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 77.0 | 77 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 78.0 | 78 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 79.0 | 79 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 80.0 | 80 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 81.0 | 81 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 82.0 | 82 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 83.0 | 83 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 84.0 | 84 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 85.0 | 85 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 86.0 | 86 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 87.0 | 87 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 88.0 | 88 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 89.0 | 89 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 90.0 | 90 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0